Abstract: The one-class support vector machines with Gaussian kernel function is a promising machine learning method which have been employed extensively in ...
Abstract—The one-class support vector machines with Gaus- sian kernel function is a promising machine learning method which have been employed extensively ...
Li et al. uses OCSVM for fault detection in closed-loop systems [19]. In the field of parameter optimization of OCSVM, Anaissi et al. proposed a new ...
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The OC-SVM with Gaussian kernel is a nonparametric estimator of a level set of the density governing the observed sample, with the parameter ν implicitly de ...
This work focuses on the one-class SVM classifier as a basis because it can scale well and can learn non-linear decision functions via kernel methods. The one- ...
May 24, 2024 · The gamma and coef0 parameters govern the shape and position of the decision boundary. Radial Basis Function (RBF) or Gaussian Kernel: The RBF ...
A novel method to solve the problem of kernel parameter selection in one-class SVM with the Gaussian kernel by measuring the distances from the samples to ...
The present invention proposes a kind of one-class support vector machines Optimization Method of Kernel Parameter based on sample edge point internal point ...
Jul 29, 2020 · This paper studies the influence of hyperparameters on the Gaussian kernel SVM when such hyperparameters attain an extreme value (0 or ∞). In ...
In this paper, we propose two new methods to select Gaussian kernel parameters in OCSVM. The first one is indirect, optimizing the Gaussian kernel parameter ...